<![CDATA[In a period of several years, the Indonesian economy has experienced low inflation in all sectors, including Indonesia's electricity and fuel. This increase in the price of electricity and household fuel can trigger inflation in other economic sectors, because these two things are necessities human tree. The purpose of this study is to analyze the application of data mining in predicting household electricity and fuel prices using the regression method. Electricity and house gas prices are important indicators related to financial stability and public health. This study uses data mining methods to identify patterns and trends in local electricity and gas prices. The linear regression method is used as an analytical tool to develop predictive models based on historical data. The dataset was obtained through the Central Statistics Agency from 2021 to 2022 which includes monthly inflation data from 90 cities throughout the year. The results of this study are predictions of annual inflation that will occur. Using data mining and linear regression methods, this research has the potential to be a useful tool for generating better home electricity and fuel price control strategies. This research can also be the basis for further research in the same or other fields.]]>
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